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Fuzzy Trust Protocol for Malicious Node Detection in Wireless Sensor Networks

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Abstract

Wireless sensor networks (WSNs) are used in many applications nowadays, because of its extensive usage. Due to the distinct characteristics, they are vulnerable to many attacks. To secure WSN, trust management plays a pertinent role. In trust based security model, decision is taken based on some specific behavior, and so it has uncertainty. Fuzzy logic deals with uncertainty and has tolerance of imprecise data with high power of precision. In this study, fuzzy logic based multi-attribute trust model is suggested. The proposed trust model has message success rate, elapsed time at node, correctness and fairness as trust metrics. Once the four trust values are calculated, fuzzy computational theory is applied to compute the final trust value of every node that can be anyone of low (l), medium (m) and high (h). Simulation results show that the fuzzy based multi-attribute trust evaluation outperforms weighted summation based multi-attribute trust evaluation.

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References

  1. Matin, M. A., & Islam, M. M. (2012). Overview of wireless sensor network. Rijeka: INTECH Open Access Publisher.

  2. Vaish, R. (2009). Application of wireless sensor networks for environmental monitoring and development of an energy efficient cluster based routing. Doctoral dissertation, National Institute of Technology Rourkela.

  3. Yick, J., Mukherjee, B., & Ghosal, D. (2008). Wireless sensor network survey. Computer networks, 52(12), 2292–2330.

    Article  Google Scholar 

  4. Stankovic, J. A., Wood, A. D., & He, T. (2011). Realistic applications for wireless sensor networks. In S. Nikoletseas & J. D. P. Rolim (Eds.), Theoretical aspects of distributed computing in sensor networks (pp. 835–863). Berlin: Springer.

    Chapter  Google Scholar 

  5. Momani, M., & Challa, S. (2010). Survey of trust models in different network domains. arXiv preprint arXiv:1010.0168.

  6. Sakthidevi, I., & Srievidhyajanani, E. (2013). Secured fuzzy based routing framework for dynamic wireless sensor networks. In International conference on circuits, power and computing technologies (ICCPCT) (pp. 1041–1046). IEEE.

  7. Xia, H., Jia, Z., & Sha, E. H. M. (2014). Research of trust model based on fuzzy theory in mobile ad hoc networks. IET Information Security, 8(2), 88–103.

    Article  Google Scholar 

  8. Xia, H., Jia, Z., Ju, L., Li, X., & Zhu, Y. (2011). A subjective trust management model with multiple decision factors for MANET based on AHP and fuzzy logic rules. In 2011 IEEE/ACM international conference on green computing and communications (GreenCom) (pp. 124–130). IEEE.

  9. Yu, L., Liu, Z., Gao, Y., & Samba, D. (2012). Trust evaluation model based on behavior space classification for ad hoc networks. Tsinghua Science and Technology, 17(2), 179–185.

    Article  Google Scholar 

  10. Luo, J., Liu, X., Zhang, Y., Ye, D., & Xu, Z. (2008). Fuzzy trust recommendation based on collaborative filtering for mobile ad-hoc networks. In 33rd IEEE conference on local computer networks (LCN) (pp. 305–311). Montreal.

  11. Xia, H., Jia, Z., Ju, L., & Zhu, Y. (2011). Trust management model for mobile ad hoc network based on analytic hierarchy process and fuzzy theory. IET Wireless Sensor Systems, 1(4), 248–266.

    Article  Google Scholar 

  12. Li, X., Jia, Z., Zhang, P., & Wang, H. (2010). A trust-based multipath routing framework for Mobile Ad hoc NETworks. In 2010 Seventh international conference on fuzzy systems and knowledge discovery (FSKD) (Vol. 2, pp. 773–777). IEEE.

  13. Liao, X. F. (2011). Research on subject trust evaluation based on fuzzy theory. In Advanced engineering forum (Vol. 1, pp. 52–56). Trans Tech Publications.

  14. Maksimovic, M., Vujovic, V., Perisic, B., & Milosevic, V. (2015). Developing a fuzzy logic based system for monitoring and early detection of residential fire based on thermistor sensors. Computer Science and Information Systems, 12(1), 63–89.

    Article  Google Scholar 

  15. Javanmardi, S., Shojafar, M., Shariatmadari, S., & Ahrabi, S. S. (2014). Fr trust: A fuzzy reputation-based model for trust management in semantic p2p grids. International Journal of Grid and Utility Computing, 6(1), 57–66.

    Article  Google Scholar 

  16. Tajeddine, A., Kayssi, A., Chehab, A., & Artail, H. (2011). Fuzzy reputation-based trust model. Applied Soft Computing, 11(1), 345–355.

    Article  Google Scholar 

  17. Bharadwaj, K. K., & Al-Shamri, M. Y. H. (2009). Fuzzy computational models for trust and reputation systems. Electronic Commerce Research and Applications, 8(1), 37–47.

    Article  Google Scholar 

  18. Alsaqour, R., Abdelhaq, M., Saeed, R., Uddin, M., Alsukour, O., Al-Hubaishi, M., et al. (2015). Dynamic packet beaconing for GPSR mobile ad hoc position-based routing protocol using fuzzy logic. Journal of Network and Computer Applications, 47, 32–46.

    Article  Google Scholar 

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Authors and Affiliations

  1. CSE Department, VV College of Engineering, Tisaiyanvilai, Tamil Nadu, India

    V. Ram Prabha

  2. Computer Science and Engineering Department, Government College of Engineering, Tirunelveli, Tamil Nadu, India

    P. Latha

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  1. V. Ram Prabha
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  2. P. Latha
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Correspondence to V. Ram Prabha.

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Ram Prabha, V., Latha, P. Fuzzy Trust Protocol for Malicious Node Detection in Wireless Sensor Networks. Wireless Pers Commun 94, 2549–2559 (2017). https://doi.org/10.1007/s11277-016-3666-1

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  • DOI: https://doi.org/10.1007/s11277-016-3666-1

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